A typical process plant, such as a chemical, utility or metallurgical plant, has hundreds of control loops. Control performance is important to ensure tight product quality and low product cost in such plants. The presence of oscillation in a control loop increases the variability of the process variables, thus causing inferior quality products, larger rejection rates, increased energy consumption, reduced average throughput and reduced profitability. The only moving part in a control loop is the control valve, or other final control element. Control valves and other final control elements frequently suffer from problems such as stiction, leaks, tight packing, and hysteresis. There are reports that about 30% of control loops are oscillatory due to control valve problems.
If the final control element contains non-linearities, such as stiction, backlash, and deadband, the final output to the process may be oscillatory which in turn can cause oscillations in the process output. Among the many types of non-linearities in control valves, stiction is the most common and has been a long-standing problem in process industry. It hinders proper movement of the valve stem and consequently affects control loop performance. Stiction can easily be detected using invasive methods such as a valve travel or a bump test. Invasive methods require stroking or traveling the valve over its full travel span when in-service or out of service. This is now called the “valve travel test” in Instrument Society of America (ISA) standards (ISA-75.13-1996; ANSI/ISA-75.05.01-2000). Using this type of test, stiction can be quantified as the amount of changes required in the control signal to move the valve from its position where it was stuck. Since it is neither feasible nor cost-effective to invasively test hundreds of valves in a plant site, non-invasive methods are preferred. There have been many invasive tests or methods suggested for analysis and performance of control valves, however relatively few non-invasive studies or methods have been proposed.
Limitations of the few prior art non-invasive methods include non-compatibility with loops involving an integrator or compressible fluids, distortion of data by noise and other physical disturbances, data influenced by process or control dynamics and the requirement of obtaining a model of the process and many tuning parameters. One such non-invasive method for detecting stiction is Horch's cross-correlation method. The Horch method (Horch, 1999; Horch et al., 2000; Horch, 2000) detects stiction with the use of the cross-correlation function between pv and op. However, this method is not applicable for processes containing an integrator, for example, a level control loop, or for loops carrying a compressible medium such as steam or air. Horch's method is mainly useful for flow control loops. Even for flow control loops, it reportedly produces inconclusive results on occasion (Desborough and Miller, 2002). Also, if there is a sinusoidal disturbance entering the control loop, the method falsely detects stiction in the control valve (Choudhury et al., 2002, 2004c). Such disturbances are not uncommon.
Moreover, all known methods of detecting stiction can only detect stiction but cannot quantify it. Therefore, there is a need in the art for a non-invasive method capable of detecting stiction and it would be preferable if such methods were also capable of quantifying stiction. Such methods may be useful in the process industry to identify valves or other final control elements that need maintenance or repair.